Python torchvision.transforms.transforms.RandomCrop() Examples

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Example #1
Source File: get_dataloader.py    From Greedy_InfoMax with MIT License 6 votes vote down vote up 
def get_transforms(eval=False, aug=None):
    trans = []

    if aug["randcrop"] and not eval:
        trans.append(transforms.RandomCrop(aug["randcrop"]))

    if aug["randcrop"] and eval:
        trans.append(transforms.CenterCrop(aug["randcrop"]))

    if aug["flip"] and not eval:
        trans.append(transforms.RandomHorizontalFlip())

    if aug["grayscale"]:
        trans.append(transforms.Grayscale())
        trans.append(transforms.ToTensor())
        trans.append(transforms.Normalize(mean=aug["bw_mean"], std=aug["bw_std"]))
    elif aug["mean"]:
        trans.append(transforms.ToTensor())
        trans.append(transforms.Normalize(mean=aug["mean"], std=aug["std"]))
    else:
        trans.append(transforms.ToTensor())

    trans = transforms.Compose(trans)
    return trans